NEUROARCHITECTURE
The Measurability of Humans Emotional and Physical Response to Built Environment
SOFIE GUSTAFSSON
NEUROARCHITECTURE
NEUROARCHITECTURE
The Measurability of Humans Emotional and Physical Response to Built Environment
MASTER THESIS
Master Thesis in Architecture Sofie Gustafsson NTNU - Spring 2021
Master Thesis in Architecture The Norwegian University of Science and Technology
Acknowledgements Preface
Reading guide Aims & Intentions Thesis Question Methodology
1. Introduction 2. Neuroscience 3. Neuroaesthetics 4. Neuroarchitecture 5. The Nervous System
6. Assessing the Quality of Research 7. Systematic Review
8. Discussion Appendix A Appendix B Appendix C i
iii v vi vii viii
1 4 16 22 32 42 50 94 98 110 125
Contents
Acknowledgements
I would like to add a few words of appreciation for the people who has been a part of this process.
First of all, to my family and friends. Especially my parents, who have always supported me with love, encouragement and patience. Without you, I could never have reached my goals. Secondly, my supervisor, Bjørn Otto Braathen and staff at NTNU whom has offered valuable advice and guidance throughout this project. Lastly, I would like to express my gratitude to the special people whom I have befriended during my eight- year-long academic journey.
Thank you all for your support.
Sofie Gustafsson ii of viii Master Thesis 2021 We shape our buildings
and afterwards our buildings shape us.
WINSTON CHURCHILL
Preface
I was initially introduced to neuroarchitecture last year. I had just moved into my new apartment and was listening to a podcast whiles unpacking.
In the podcast, a ‘neurodesigner’ was talking about her new book called
‘Designfulness’. She explained how recent discoveries in neuroscience have led to a better understanding of how architecture and design affect our well-being. The wet autumn weather and ongoing pandemic kept me indoors most of the time, and I started to reflect on how the interior environment affected my mental health. I was intrigued by what I just had learned and ordered the book the same night.
This was the beginning of an insightful, but at times also overwhelming journey. When I started my thesis work, I knew close to nothing about neuroarchitecture and had no previous experience in writing systematic reviews. Looking back, I could not have imagined the amount of work this project required. I have spent countless hours learning about neuroscience, study designs, statistics, academic writing, and I have read hundreds of research papers. It has been a very rewarding and interesting experience, but also challenging at times. There is currently no staff or researchers at the Faculty of Architecture and Design at NTNU that have experience in neuroarchitecture, which limited the availability of support and supervision.
Initially, I planned to perform experiments and conduct a study. The experiment was planned to use EEG to collect data from test persons visiting IKEA and the Nidaros Cathedral, and then study how the participants experienced the two contrasting spaces. After consulting a professor in neuroscience at the faculty of medicine and health sciences, NTNU, I sadly had to accept that it would not be possible to perform the experiment due to the current pandemic and the restrictions that made the involvement of test persons impossible.
Until recently, there have been very few studies on intuitive design and human responses to environmental stimuli. However, discoveries in neuroscience have provided data that gives us a physiological understanding of how the brain helps us navigate and react in built environments. Architects and neuroscientists are now working together using neurofeedback equipment to gather and then analyse data. The new field of evidence-based neuroarchitecture relies on neuroscience when making design decisions. This thesis provides an insight into the field of neuroarchitecture and how architects can benefit from recent scientific discoveries.
Sofie Gustafsson iv of viii Master Thesis 2021 Design is a frame for life.
ILSE CRAWFORD
Reading guide
The first six chapters are mainly theoretical and are included as an introduction to neuroarchitecture. Some information from the first chapters will be repeated in the systematic review for clarifying and informative purposes.
The systematic review is the main body of work. It is highly advised to read the appendices referred to in the review to fully understand the work.
The concluding chapter is a personal reflection on my findings and how I believe that neuroarchitecture can benefit the built environment in the future.
Sofie Gustafsson vi of viii Master Thesis 2021
Aims & Intentions
Neuroscience and Architecture are both comprehensive and complex fields involving a number of professions. The aim of this master thesis is to get a greater understanding of these two fields and how they come together to forms neuroarchitecture.
The subject I want to explore in my work is the cognitive and behavioural impact of spatial and architectural design. This thesis aims to study historical theories concerning the built environment and the human brain, subjective and objective measuring methods that are used to measure human responses to environmental stimuli and to evaluate to what degree neuroscience can contribute to improving architectural design.
Neuroarchitecture has become a trend that is portrayed by certain professionals and by the media as the ‘solution’ in creating ideal architecture. The history of architectural design does however tell us that such ‘trends’ can have a devastating outcome. By identifying aspects within Neuroarchitecture that can contribute and limit architectural design I will try to assess what role Neuroarchitecture will have in the future of architectural design.
Thesis Questions
What theories and methodologies exist and are appropriate to measure human responses to environmental stimuli?
What are the best suited quantitative research method to gather data for future studies in neuroarchitecture?
What findings are emerging from evidence-based studies, and to what degree can neuroscience contribute to improve architectural design in the future?
Sofie Gustafsson viii of viii Master Thesis 2021
Methodology
I will first study and describe the brains anatomy and physiology, objective feedback techniques and subjective assessment methods. I will also explore how neuroarchitecture has developed since it was first described.
The information will be gathered through literature research and online courses/ lectures.
I will then perform a systematic literature review to identify studies that are relevant to the topic, as well as to determine the prospects of further research. An iterative systematic approach will be used to assess the importance of specific criteria. This will help to define words that will be used in the literature search and distinguish relevant material.
Lastly, I will review and discuss my findings and what they tell about the limitations, contributions and future of neuroarchitecture.
Sofie Gustafsson Master Thesis 2021 NeuroScience
A multilevel, multidisiplinary subject comprising morphological, functional and physical studies of the central nervous system
(Shulman 2013, p. 59)
NeuroAesthetics
A relatively young field within cognitive neuroscience, concerned with the neural underpinnings of aesthetic experience
of beauty, particularly in visual art (Chinzia 2009, p. 682)
NeuroArchitecture
Neuro-architecture unites architecture and neuroscience to better understand the relationship between the human brain
and the surrounding built environment (Azzazy, 2020, p. 3)
1. Introduction
Architecture has the ability to merge perception, imagination and experience with the tangible spatiality. Since the dawn of human dwelling, intuition has been a key in creating environments where humanity can prosper. Theories about the relationship between ‘the mind and the body’ and ‘the body and space’, as well as the connects between architecture and anatomy, physiology, psychology, phenomenology and intuition have historically been of great human interest.
People spend most of their time surrounded by the built environment, from birth throughout life and ultimately death. Research shows that Europeans spend almost 22 hours a day indoors (World Health Organization regional office for Europe, 2013). Cities are continuously growing, and two-thirds of the world’s population will live in urban areas by 2050. Consequently, the urban area will expand significantly to provide shelter and facilities for the 2.4 billion new inhabitants (Goldhagen and Gallo, 2017, United Nations Department of Economic and Social Affairs, 2018). Therefore, it has never been more critical than now to create sustainable built environments that promote good health and well-being.
In a world where we spend most of our time indoors, and climate changes and social issues have become a frightening reality, we can no longer afford to waste resources on unsustainable architecture. Humans need to constantly adapt to the built environment and all multisensory stimuli it entails. Neuroarchitecture can potentially give scientific insight into human response patterns in built environments. Such findings can inform architects during the design process and consequently positively impact the future of the built environment. Better knowledge about humans’
cognitive and emotional responses to the built environments could be used to improve inhabitants’ physical and mental health. Additionally, it may result in more efficient use of space with a beneficial impact on the building’s functionality, quality, sustainability, and the economy.
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GOLDHAGEN, S. W. & GALLO, A. 2017. The Sorry Places We Live. Welcome to your world:
How the built environment shapes our lives. Harper New York.
UNITED NATIONS DEPARTMENT OF ECONOMIC AND SOCIAL AFFAIRS 2018. World Urbanization Prospects: The 2018 Revision New York: United Nations.
WORLD HEALTH ORGANIZATION REGIONAL OFFICE FOR EUROPE 2013. Combined or multiple exposure to health stressors in indoor built environments. In: SARIGIANNIS , D.
A. (ed.) An evidence-based review prepared for the WHO training workshop “Multiple environmental exposures and risks“. World Health Organization.
References
Sofie Gustafsson 4 of 127 Master Thesis 2021 The ultimate challenge—is to
understand the biological basis of consciousness and the brain processes
by which we feel, act, learn, and remember.
ERIC R. KANDEL
2. Neuroscience
The mind has always fascinated humans. Quests to understand the brain dates back to early Greek and Egyptian civilisations. Ancient Greek history indicates that the nervous system was discovered already in the 3rd Century BC. Alcmaeon of Croton’s medical writings, Praxagoras of Kos, theories involving neurons, and Herophilus of Chalcedon distinguishment between sensory and motor nerves are essential to our understanding of the brain and the nervous system (Panegyres and Panegyres, 2016).
A significant number of discoveries have since been made in the rapidly evolving field that we now know as neuroscience. A brief introduction to some historical findings that are relevant for both neuroarchitecture and the Norwegian University of Science and Technology (NTNU) are mentioned below:
Charles Darwin’s was an English naturalist, geologist and biologist who made significant contributions in several scientific fields. Darwin’s scientific theory of evolution by natural selection is considered the foundation of modern evolutionary synthesis. In 1873 Darwin suggested that animals navigate by using information about their own movement (self-motion cues) to determine their location in relation to the starting position (Whishaw et al., 2001).
Paul Broca was a French surgeon, anatomist and anthropologist. He is known best known for his contribution to the foundation of modern neuropsychology and cognitive neuroscience. In the 1860s, Broca studied patients with brain damage and found that different brain regions are responsible for specific functions. Broca’s area is a region in the frontal lobe and is named after Broca due to his discoveries involving language expression (Cowan et al., 2000, Dronkers et al., 2007).
Sofie Gustafsson 6 of 127 Master Thesis 2021 RAT
HIPPOCAMPUS
(Place cell location) ENTORHINAL CORTEX
(Grid cell location)
Figure 1 - The firing pattern of place cell and grid cells.
Adapted from Bjerknes and Moser, 2019
HUMAN
Hippocampus Entorhinal Cortex
John O’Keefe and John Dostrovsky studied hippocampal function and memory in the 70s and were able to record the activity of hippocampal neurons (place cells) in rats. Each individual place cell fired when a rat was in a specific location, and combined, they created a representation of the entire space that the rat was occupying (O’Keefe and Dostrovsky, 1971). Further research also showed that the hippocampus is a
structure that serves as an internal representation of the surrounding environment (cognitive map, O’keefe and Nadel, 1978).
Around 130 years after Darwin first voiced his theory, May-Britt Moser and Edvard Moser discovered the brain region that is specialised in navigation. The two scientists at NTNU described the grid cells (also present in humans) in the hippocampus’ input region of the brain, the entorhinal cortex. Recordings of a moving rodent within an enclosed space showed that a grid cell responds when the rodent is in a particular location. Those locations are spaced out and creating a hexagonal firing pattern that forms virtual maps of the surrounding environment (Moser et al., 2015).
Grid cells can also explain how memories are formed and how humans can envision spaces that they have previously visited (Abbott, 2014).
In 2014 John O’Keefe, May-Britt Moser and Edvard Moser were awarded the Nobel prize in Physiology or Medicine for discovering the function of these cells dealing with location and space, the “GPS system” of the brain.
Neuroscience is multidisciplinary and includes various fields, such as biology, genetics, medicine, psychology, chemistry, computer science, engineering, and mathematics. During recent years many discoveries and advances have been made due to the rapid progress and increase of technology (Kaiser, 2014). New scientific findings have provided a greater understanding of human psychological and behavioural needs and the functions of the pathological nervous system. The Society for Neuroscience predicts that this rapid growth will continue during the next 50 years, and new advances can improve human health, the economy, and society (Altimus et al., 2020).
Sofie Gustafsson 8 of 127 Master Thesis 2021
Implicit
Technique Measure’s: Temporal resolution Spatial
resolution Neural
signal Invasive Method type Training Cost Portability
EEG Electrical High
(1-4ms) Low
(~10mm) Direct No Non-invasive Some Low Stationary/
portable
ECoG Electrical High
(~3 ms)
High
(~1mm) Direct Yes Invasive Extensive High Stationary/
portable
ICNR Electrical High
(~3 ms)
High
(~0.5mm)* Direct Yes Invasive Extensive High Stationary/
portable
PET Metabolic Low
(≥10s)
High
(~5 mm) Indirect Yes Non-invasive Extensive High Stationary
fMRI Metabolic Low
(1s)
High
(~1mm) Indirect No Non-invasive Extensive High Stationary
NIRS Metabolic Low
(1s)
High
(~5mm) Indirect No Non-invasive Some Low Stationary/
portable
MEG Magnetic High
(~5ms)
High
(~5mm) Direct No Non-invasive Extensive High Stationary
Table 1 - Common functional brain imaging techniques.
(iMotions, 2019, Koike et al., 2013, McLoughlin et al., 2014, Pandarinathan et al., 2018) EEG = Electroencephalogram
EcoG = Electrocorticography
ICMR = Intra-cortical neuronal recording PET = Positron emission tomography fMRI = Functional magnetic resonance imaging MEG = Magnetoencephalography
NIRS = Near-infrared spectroscopy
CLASSIFICATION OF NEUROLOGICAL INSTRUMENTS
fMRI
NIRS
EEG Skin
Conductance
Facial Coding
PET MEG
ECoG ICMR
Eye Tracking
Physical activity Recording Electrical Activities in Brain No Recording of Brain Activities Recording Metabolic Activities in Brain
Figure 2 - Classification of Neurological Instruments.
Functional imaging techniques, processor technologies, data analysis procedures, and algorithms have allowed researchers to better understand how the brain functions (iMotions, 2019). There are a variety of functional imaging techniques available, which are used for scientific, medical, educational and commercial purposes (see Table 1, p. 8). Substantial amounts of resources have been granted to the field of neuroscience in the quest to get a better understanding of human behaviour, experience and related diseases. Neuroscience is currently one of the most active areas of contemporary biology and medicine (Mancall and Brock, 2011). The new scientific advances have caught both scientists and the general public’s attention. New discoveries will contribute to a better understanding the of organisation and function of the brain and consequently the treatment of mental and neurological disorders (Quaglio et al., 2017) The development of functional imaging techniques, processor technologies, data analysis procedures, and algorithms have allowed researchers to investigate the brain functions in greater detail (iMotions, 2019).
Some of the most common functional brain imaging technique are listed in Table 1, p.8.
Temporal resolution: How closely the measured activity corresponds to the timing of the actual neural activity.
Spatial resolution: How the accurately the measured activity is localized within the brain (Cohen, 2009).
2.1. Functional Imaging Techniques
Sofie Gustafsson 10 of 127 Master Thesis 2021
Band Symbol Lower (Hz) Upper (Hz) Amplitude Range (µV)
Delta δ 0.5 4 20-200
Theta θ 5 7 20-100
Alpha α 8 14 20-60
Beta β 15 30 2-20
Gamma γ 30 50* 5-10
Table 2 - Normal Frequency Range of Ongoing EEG (in Hz, Cycles per second) Based on information from Hughes, 2008
*40 Hz is typically used, although some have reported that gamma can range up to 100 Hz.
Figure 3 - Brain wave samples for different waveforms.
(Abhang et al., 2016)
GAMMA
BETA
ALPHA
THETA
DELTA
Problem solving, concentration
Busy, active mind
Reflective, restful
Drowsiness
Sleep, dreaming
2.2. Electroencephalogram (EEG)
In recent years there has been a rapid development of EEG equipment due to new and innovative digital technology. Today, EEG is a widely used method to analyse brain function in research and to diagnose medical conditions such as epilepsy and sleep disorders (Da Silva, 2009). EEG equipment has become a popular tool as it is relatively inexpensive, can be mobile, and is relatively easy to use.
EEG offers continuous recording of brain activity by measuring the differences in voltage (electrical potential) between two electrodes (see Table 2, p. 10). It is a non-intrusive method where electrodes are attached to the scalp. Modern EEG has a millisecond temporal resolution, and this means that it can produce thousands of images per second of the electrical activity from multiple electrodes. A disadvantage with EEG is its poor spatial resolution. The electrodes record the electrical activity from the scalp (surface) and cannot determine the exact source of the activity.
However, advances in EEG acquisition systems and electric head modelling (3D models showing in which parts of the brain the activity takes place) have improved the spatial resolution of scalp EEG (Ferree et al., 2001).
High-density EEG recording (64 - 256 channels) offers a higher number of solution points and therefore more spatial resolution, and somewhat better spatial accuracy. The accuracy, however, stops improving when the solution points exceed a certain number as the number of electrodes determines the quantity of input (Michel and Brunet, 2019).
The number of electrodes varies from 10 to several hundred, depending on the equipment and the size of the experiment. Several factors affect the price and accuracy of the EEG equipment. More expensive equipment usually has more electrodes, advanced digitalising software and an amplifier with higher sampling rates (Abreu et al., 2018, iMotions, 2019).
A range of technology and equipment is necessary to record reliable EEG data, including devices to deliver stimuli, an EEG headset to record brain activity, an EEG amplifier, and a computer to amplify, filter, and convert analogue electrical signals from the sensor into digital signals.
The electrode that captures brainwave activity is called an EEG channel, and the number of channels determines the density (more detailed information) of the EEG recording.
Artefacts in EEG are signals recorded by EEG but not generated by the brain. EEG data can become affected by a variety of different artefacts that originate from internal and external sources. Internal sources of artefacts are caused by physiological activity and movement, while external sources of artefacts are due to environmental interferences, the recording equipment, electrode popping and cable movement. (Islam et al., 2016).
Sofie Gustafsson 12 of 127 Master Thesis 2021
AMPLIFIER
PROCESSING
FEATURE EXTRACTION
FEATURE SELECTION
CLASSIFICATION Electrode
Measured potentials from each electrode
Raw EEG data
Figure 4 - EEG Recording of waveforms.
EEG data analysis
Voltage: Symbol V. An electromotive force or potential difference expressed in volts.
Volt: Symbol V. The SI unit of electric potential, potential difference, or electromotive force defined as the difference of potential between two points on a conductor carrying a constant current of one ampere when the power dissipated between the points is one watt. It is named after Alessandro Volta.
Currents: Symbol I. A flow of electric charge through a conductor. The current at a particular cross section is the rate of flow of charge. The charge may be carried by electrons, ions, or positive holes. The unit of current is the ampere.
Resistance: Symbol R. The ratio of the potential difference across an electrical component to the current passing through it. It is thus a measure of the component’s opposition to the flow of electric charge. In general, the resistance of a metallic conductor increases with temperature, whereas the resistance of a semiconductor decreases with temperature.
Frequency: Symbol f or v. The rate of repetition of a regular event. The number of cycles of a wave, or some other oscillation or vibration, per second is expressed in hertz (Hz), cycles per second.
Power: Symbol P. The rate at which work is done or energy is transferred.
In SI units it is measured in watts (joules per second).
Phase: A description of the stage that a periodic motion has reached, usually by comparison with another such motion of the same frequency.
Two varying quantities are said to be in phase if their maximum and minimum values occur at the same instants; otherwise, there is said to be a phase difference.
(Rennie and Law, 2019)
Terminology
Sofie Gustafsson 14 of 127 Master Thesis 2021
Tables & Figures
Table 1 - Common functional brain imaging techniques.
(iMotions, 2019, Koike et al., 2013, McLoughlin et al., 2014, Pandarinathan et al., 2018)
Table 2 - Normal Frequency Range of Ongoing EEG (in Hz, Cycles per second)
(Hughes, 2008)
Figure 1 - The firing pattern of place cell and grid cells.
Adapted from Bjerknes and Moser, 2019
Figure 2 - Classification of Neurological Instruments.
Figure 3 - Brain wave samples for different waveforms.
(Abhang et al., 2016)
Figure 4 - EEG Recording of waveforms.
8
10
6
8 10
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ABBOTT, A. 2014. Neuroscience: Brains of norway. Nature News, 514, 154.
ABREU, R., LEAL, A. & FIGUEIREDO, P. 2018. EEG-Informed fMRI: A Review of Data Analysis Methods. Frontiers in Human Neuroscience.
ABHANG, P. A., GAWALI, B. W. & MEHROTRA, S. C. 2016. Chapter 2 - Technological Basics of EEG Recording and Operation of Apparatus. In: ABHANG, P. A., GAWALI, B. W. & MEHROTRA, S. C. (eds.) Introduction to EEG- and Speech-Based Emotion Recognition. Academic Press.
ALTIMUS, C. M., MARLIN, B. J., CHARALAMBAKIS, N. E., COLÓN-RODRÍGUEZ, A., GLOVER, E. J., IZBICKI, P., JOHNSON, A., LOURENCO, M. V., MAKINSON, R. A., MCQUAIL, J., OBESO, I., PADILLA-COREANO, N. & WELLS, M. F. 2020. The Next 50 Years of Neuroscience. The Journal of Neuroscience, 40, 101-106.
BJERKNES, T. L. & MOSER, M. 2019. A sense of place. Biologist, 66, p. 10-13.
COHEN, M. Electricity and Magnetism: Insights into the brain from multimodal imaging. 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, 2009. IEEE, 1593-1597.
COWAN, W. M., HARTER, D. H. & KANDEL, E. R. 2000. The Emergence of Modern Neuroscience: Some Implications for Neurology and Psychiatry. Annual Review of Neuroscience, 23, 343-391.
DA SILVA, F. L. 2009. EEG: origin and measurement. EEg-fMRI. Springer.
DRONKERS, N. F., PLAISANT, O., IBA-ZIZEN, M. T. & CABANIS, E. A. 2007. Paul Broca’s historic cases: high resolution MR imaging of the brains of Leborgne and Lelong. Brain, 130, 1432-1441.
FERREE, T. C., CLAY, M. T. & TUCKER, D. M. 2001. The spatial resolution of scalp EEG. Neurocomputing, 38-40, 1209-1216.
HUGHES, J. R. 2008. A review of recent reports on autism: 1000 studies published in 2007. Epilepsy & Behavior, 13, 425-437.
IMOTIONS 2019. Electroencephalography - The Complete Pocket Guide. iMotions.
ISLAM, M. K., RASTEGARNIA, A. & YANG, Z. 2016. Methods for artifact detection and removal from scalp EEG: A review.
Neurophysiol Clin, 46, 287-305.
KAISER, U. B. 2014. Editorial: advances in neuroscience: the BRAIN initiative and implications for neuroendocrinology.
Molecular endocrinology (Baltimore, Md.), 28, 1589-1591.
KOIKE, S., NISHIMURA, Y., TAKIZAWA, R., YAHATA, N. & KASAI, K. 2013. Near-Infrared Spectroscopy in Schizophrenia: A Possible Biomarker for Predicting Clinical Outcome and Treatment Response. Frontiers in Psychiatry, 4.
MANCALL, E. L. & BROCK, D. G. 2011. Overview of the Organization of the Nervous System. Gray’s Clinical Neuroanatomy:
The anatomic basis for clinical neuroscience Elsevier Health Sciences.
MCLOUGHLIN, G., MAKEIG, S. & TSUANG, M. T. 2014. In search of biomarkers in psychiatry: EEG‐based measures of brain function. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 165, 111-121.
MICHEL, C. M. & BRUNET, D. 2019. EEG source imaging: a practical review of the analysis steps. Frontiers in neurology, 10, 325.
MOSER, M.-B., ROWLAND, D. C. & MOSER, E. I. 2015. Place cells, grid cells, and memory. Cold Spring Harbor perspectives in biology, 7, a021808.
O’KEEFE, J. & DOSTROVSKY, J. 1971. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely- moving rat. Brain Research, 34, 171-175.
O’KEEFE, J. & NADEL, L. 1978. The hippocampus as a cognitive map, Oxford: Clarendon Press.
PANDARINATHAN, G., MISHRA, S., NEDUMARAN, A. M., PADMANABHAN, P. & GULYÁS, B. 2018. The potential of cognitive neuroimaging: a way forward to the mind-machine interface. Journal of Imaging, 4, 70.
PANEGYRES, K. P. & PANEGYRES, P. K. 2016. The Ancient Greek discovery of the nervous system: Alcmaeon, Praxagoras and
References
Sofie Gustafsson 16 of 127 Master Thesis 2021
Figure 1 - What is beauty?
(Da Vinci, 1503-1519)
3. Neuroaesthetics
Neuroaesthetics is studies on the biological mechanisms and psychological processes evoked by aesthetic experiences (Pearce et al., 2016).
Art reflects culture, society, religion, community, place and periods in time. These factors create aesthetic diversity and make art relatable to larger groups of people. Art itself might not be universal, but art as a whole is. Humans are not programmed to respond to art in a given way but are drawn to familiar and relatable objects (Nadal and Chatterjee, 2019).
German psychologist Gustav Theodor Fechner published the article ‘Das Associationsprincip in der Aesthetik’ (The Aesthetic Association Principle) in 1866 (Heidelberger, 2004, Ortlieb et al., 2020). Fechner argued that aesthetic choices are determined by the observer’s previous experiences (associative factors) and by the object’s formal properties (direct factors).
Beauty
The quality of being pleasing, especially to look at, or someone or something that gives great pleasure, especially when you look at it. Cambridge dictionary.
Artists and philosophers have debated the relationship between beauty and goodness for centuries.
Recent neuroscientific evidence supports the idea that the function of aesthetic and moral judgement shares neural pathways. However, these studies are based on assumption and historical and philosophical discussions and not neuroscientific facts (Zaidel and Nadal, 2011).
Another study found a connection between the brain’s judgement of attractiveness and goodness. In the experiments, judgment of
‘attractiveness’ and ‘goodness’ was measured separately, which could have affected the outcome of the fMRI data (Tsukiura and Cabeza, 2011).
Anjan Chatterjee, neuroscientist and professor at the University of Pennsylvania, is one of the world-leading experts in the field. His research team has studied how the brain reacts to different environments, and the neural effects caused by aesthetic experiences. Chatterjee states that there are many questions that have not been answered yet and technical advances and more research is required (Chatterjee, 2014).
Sofie Gustafsson 18 of 127 Master Thesis 2021 Natural Scientific
Approach
Biology
Chemistry Psychology Philosophy Physics /
maths
Architecture Art Assumptions
and scientific approach
Neuroarchitecture
Figure 2: The relationship between neuroscience, neuroaesthetics and neuroarchitecture.
I argue that neuroaesthetics is a subfield of neuroarchitecture as it is only focusing on the visual and aesthetic experiences of an object, whilst neuroarchitecture comprehends the visual, spatial, auditory, olfactory,
tactile and social aspects of a space (see Figure 2, p. 18).
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Figures
Figure 1 - What is beauty?
Da Vinci, 1503-1519
Figure 2: The relationship between neuroscience, neuroaesthetics and neuroarchitecture.
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CHATTERJEE, A. & VARTANIAN, O. 2014. Neuroaesthetics. Trends in Cognitive Sciences, 18, 370-375
DA VINCI, L. 1503-1519. Mona Lisa [Painting], The Mona Lisa Foundation, Available: http://monalisa.org/2012/08/16/the-earlier- version-through-the-magnifying-glass-2 [Accessed 20 April 2021
HEIDELBERGER, M. 2004. ‘Life and Work’. Nature from Within: Gustav Theodor Fechner and His Psychophysical Worldview.
Pittsburgh: University of Pittsburgh Press.
NADAL, M. & CHATTERJEE, A. 2019. Neuroaesthetics and art’s diversity and universality. Wiley Interdisciplinary Reviews- Cognitive Science, 10.
ORTLIEB, S. A., KUGEL, W. A. & CARBON, C. C. 2020. Fechner (1866): The Aesthetic Association Principle-A Commented Translation. I-Perception, 11.
PEARCE, M. T., ZAIDEL, D. W., VARTANIAN, O., SKOV, M., LEDER, H., CHATTERJEE, A. & NADAL, M. 2016. Neuroaesthetics:
The cognitive neuroscience of aesthetic experience. Perspectives on psychological science, 11, 265-279.
TSUKIURA, T. & CABEZA, R. 2011. Shared brain activity for aesthetic and moral judgments: implications for the Beauty-is- Good stereotype. Social Cognitive and Affective Neuroscience, 6, 138-148.
ZAIDEL, D. W. & NADAL, M. 2011. Brain intersections of aesthetics and morals: perspectives from biology, neuroscience, and evolution. Perspectives in Biology and Medicine, 54, 367-380.
References
Sofie Gustafsson 22 of 127 Master Thesis 2021
Figure 1: The multisensory brain.
TOUCH
HEARING
STIMULI SENSATION PERCEPTION WORKING MEMORY LONG TERM
MEMORY
RESPONSE VISION
SMELL
Figure 2: The brain’s perception process.
4. Neuroarchitecture
Since the dawn of human dwelling, intuition has been a key in creating environments where humanity can prosper. Theories about the relationship between ‘the mind and the body’ and ‘the body and space’, and the connections between architecture and anatomy, physiology, psychology, phenomenology, and in-tuition, have historically been of great human interest. The term ‘architectural determinism’ was first used by the British planner Maurice Broady. In the article, ‘The Social Context Of Urban Planning’ (1969) Broday claims that the built environment can predict and determine social behaviour. Few professionals have since adopted this somewhat controversial idea, but many architects have voiced beliefs that architecture can affect human behaviour and wellbeing.
Subjective experiences and intuitive judgment have traditionally supported architectural theories and decisions. However, the development of research methods and technology has made it possible to incorporate scientific evidence in the architectural decision-making process.
Architects and psychologist have, through empirical research, studied the correlation between human behaviour and the build environments since the 20th century (De Paiva and Jedon, 2019). Experience-based research uses assumptions to make conclusions regarding human behaviour, but not evidence-based data from experimental studies. The field of neuroarchitecture allows architects, psychologists, neuroscientists, and other disciplines to work together and investigate the short- and long- term cognitive and emotional impact of architectural spaces.
The brain has been described as “the most complex thing in the universe”
(Pacitti et al., 2019) and it is intricate in both structure and function.
Traditionally, the term ‘neuroarchitecture’ was used in neuroscience to describe the brain’s form and function (Eberhard, 2009). The expression has been adopted by architects and neuroscientists and is now used to describe a multidisciplinary research field in which the relationship between the human brain and the built environment is studied (Azzazy et al., 2020). Neuroarchitecture thus connects the fields of neuroscience and architecture. Studies based on measurable neurological findings are relatively new, and the field of neuroarchitecture is rapidly evolving as new diagnostic methods develop. This opens up for new research and many intriguing hypotheses are yet to be tested.
There has recently emerged a growing interest regarding the mind’s response to multisensory stimuli (Cross and Ticini, 2012, Spence, 2020).
The temporoparietal junction (TPJ) is a cortical region of the brain that
Sofie Gustafsson 24 of 127 Master Thesis 2021 We must therefore avoid saying that
our body is in space, or in time. It inhabits space and time.
JUHANI PALLASMAA
self-location, also described as the ability to place and experience oneself in a physical space (Aglioti and Candidi, 2011). Multisensory integration is how the combined stimuli from different sensory systems affect processes in the nervous system (Stein et al., 2009). Multisensory stimuli should therefore be considered as necessary when doing experiments involving spatial environments.
Neuroarchitecture aims to better understand human neurophysiological and psychological responses to the built environment. EEG has become one of the most popular methods to record changes in brain activity both in neuroarchitecture and in other related fields. The technology is inexpensive and assessable, and the procedure is unintrusive. Electrical activity (Hz) is recorded via electrodes attached to the scalp. However, recording a person’s emotional state has proven to be a complex task (Mauss and Robinson, 2009).
Like the Savanna Hypothesis, some theories argue that there are universal similarities regarding human aesthetic preferences (Joye, 2007).
The brain’s ability to read and understand a place has been essential for human survival and existence through history. Much of what we as humans take for granted today, such as modern surroundings, urban environments, and digitalisation, has only existed for a short moment in time. Sjövall explains that if human existence has lasted one day, humans have spent twenty-three hours and fifty-nine seconds on the African Savanna and only a fraction of the last minute in modern surroundings.
Human spatial preferences are linked to the ancient parts of the brain and are still influenced by the will to survive on the Savanna either as a hunter or gatherer (Sjövall, 2020). However, the human brain is also plastic and can to some degree change its function to meet new challenges. The modern parts of the brain have evolved and significantly grown both in size and complexity since the time spent on the Savanna and has even been described as “the most complex thing in the universe” (Pacitti et al., 2019).
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Figure 3 - The Salk Institute.
Daniels, 2017
Salk Institute for Biological Studies
Jonas Salk encouraged collaboration between architects and researchers in the 1960s, long before the field of neuroarchitecture was established.
Salk had spent many years in a laboratory, trying to find a cure for polio.
Eventually, he decided to visit a 13th-century Franciscan monastery to clear his mind. During his stay at the monastery, Salk came to important insights that led to the discovery of the polio vaccine.
Salk later collaborated with architect Louis Kahn to design the Salk Institute, as he believed that the built environment can enhance creative ability (Sternberg and Wilson, 2006).
Sofie Gustafsson 28 of 127 Master Thesis 2021 What is it about a designed space that affects the human brain and how
might understanding the response of the brain lead us to improvements in architecture in the future?
(Doughertya 2013, p. 5)
New findings in the field of Neuroarchitecture can potentially give scientific exploitations to human response patterns in built environments. Such findings can inform architects during the design process and consequently have a positive impact on the future of the built environment.
More specific:
Users physical and mental health and a more efficient use of space will have a beneficial impact on the buildings functionality, quality, sustainability and materiality as well as on the economy and environment.
Why is Neuroarchitecture important?
I believe that the future of this discipline is bright, and that neuroscientists and psychologists can foster good understanding of the needs of architects, designers and city planners to help them realise their visions in more successful ways.
Dr. Oshin Vartanian
There is, however, a risk that neuroarchitecture will become just another buzzword, a passing architectural fashion or a marketing exercise just as ’eco’,
’green’ and ’sustainable’ have become.
Ian Ritchie
NeuroArchitecture
- the future of architecture?
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Figures
Figure 1 - The multisensory brain.
Figure 2 - The brain’s perception process.
Figure 3 - Figure 3 - The Salk Institute.
Daniels, 2017 22
22
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AZZAZY, S., GHAFFARIANHOSEINI, A., GHAFFARIANHOSEINI, A., NAISMITH, N. & DOBORJEH, Z. 2020. A critical review on the impact of built environment on users’ measured brain activity. Architectural Science Review, 1-17.
BROADY, M. 1969. The social context of urban planning. Urban affairs quarterly, 4, 355-378.
BUKOWSKI, H. & LAMM, C. 2017. Temporoparietal Junction. In: ZEIGLER-HILL, V. & SHACKELFORD, T. K. (eds.) Encyclopedia of Personality and Individual Differences. Cham: Springer International Publishing.
CROSS, E. S. & TICINI, L. F. 2012. Neuroaesthetics and beyond: new horizons in applying the science of the brain to the art of dance. Phenomenology and the cognitive sciences, 11, 5-16.
DANIELS, E. 2017. Restoration work completes on Louis Kahn’s Salk Institute in California. https://www.dezeen.com/2017/07/06/
salk-institute-restoration-biological-studies-louis-khan-restoration-wje-getty-conservation-institute/.
DE PAIVA, A. & JEDON, R. 2019. Short-and long-term effects of architecture on the brain: Toward theoretical formalization.
Frontiers of Architectural Research, 8, 564-571.
DOUGHERTY, B. O. & ARBIB, M. A. 2013. The evolution of neuroscience for architecture: introducing the special issue.
Intelligent Buildings International, 5, 4-9.
EBERHARD, J. P. 2009. Applying Neuroscience to Architecture. Neuron, 62, 753-756.
IONTA, S., HEYDRICH, L., LENGGENHAGER, B., MOUTHON, M., FORNARI, E., CHAPUIS, D., GASSERT, R. & BLANKE, O.
2011. Multisensory Mechanisms in Temporo-Parietal Cortex Support Self-Location and First-Person Perspective. Neuron, 70, 363-374.
JOYE, Y. 2007. Architectural lessons from environmental psychology: The case of biophilic architecture. Review of general psychology, 11, 305-328.
MAUSS, I. B. & ROBINSON, M. D. 2009. Measures of emotion: A review. Cognition & emotion, 23, 209-237.
PACITTI, D., PRIVOLIZZI, R. & BAX, B. E. 2019. Organs to Cells and Cells to Organoids: The Evolution of in vitro Central Nervous System Modelling. Frontiers in Cellular Neuroscience, 13.
RITCHIE, I. 2021. Neuroarchitecture: Designing with the Mind in Mind, John Wiley & Sons.
SJÖVALL, I. 2020. Back to Basics. In: ÅKESSON, B. (ed.) Designfullness. Stockholm, Sweden: Bokförlaget Langenskiöld.
SPENCE, C. 2020. Senses of place: architectural design for the multisensory mind. Cognitive Research: Principles and Implications, 5, 1-26.
STEIN, B. E., STANFORD, T. R. & ROWLAND, B. A. 2009. The neural basis of multisensory integration in the midbrain: Its organization and maturation. Hearing Research, 258, 4-15.
References
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Nervous system
Central nervous system
(Cerebrum, cerebellum and spinal cord)
Peripheral nervous system
(Cranial and spinal nerves)
Autonomic nervous system
(Controls involuntary muscles)
Sympathetic division
(Arousing)
Sensory neurons
(Sensory input)
Parasympathetic division
(Calming)
Motor neurons
(Motor output)
Somatic nervous system
(Controls voluntary muscles)
Figure 1 - An overview of the CNS and the PNS.
Adapted from Djebbara, 2020
5. The Nervous System
The complexity of the human nervous system is both evidence and a product of the biological evolution (Mancall and Brock, 2011). The brain is involved in most processes in the human body.
The brain’s functions involved: select, sorts, and interprets information from the body and the environment, determine the body’s internal and external behaviour (Brodal, 2010b).
The nervous system is subdivided into the central nervous system (CNS) and the peripheral nervous system (PNS):
• The CNS is made up of the brain (cerebrum and cerebellum) and the spinal cord.
• The PNS is made up of nerves that extend from the brain and spine, which makes it possible for the central nervous system to communicate with the body. (Brodal, 2010a). The PNS is further split into the somatic nervous system (SNS) and the autonomic (visceral) nervous system (ANS):
• The ANS is associated with all structures excluding, the skeletal muscle (associated with the SNS). This includes regulation of involuntary movements such as cardiac function, respiration and other reflexes (Rea, 2015).
• The SNS comprises all nerves that run to and from the spinal cord and are associated with skin and voluntary movements via skeletal muscles (Kapalka, 2010). Sensory (afferent) neurons receive stimuli from outside the CNS and convert them into internal electrical impulses, whiles motor (efferent) neurons transmits signals from the brain and spinal cord to muscle cells (Rea, 2015).
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Figure 2 - The brains anatomy.
Adapted from iMotions, 2019
Cerebellum
Brainstem Cerebrum
The Cerebrum
The cerebrum (front of the brain) is the largest part of the human brain in volume. The ovoid-shaped brain area occupies most of the cranial cavity.
It is folded and consists of two hemispheres that are nearly separated by a vertical slit. The corpus callosum is a bundle of nerve fibres that forms a bridge, carries information, and connects the cerebral hemispheres. The right hemisphere processes the signals from the left side of the body, and the left hemisphere processes signals from the right side of the body. The cerebrum enables consciousness as well as sensory and motor processing such as initiation- and coordination of movement, temperature, touch, vision, hearing, judgment, reasoning, problem-solving, emotions, and learning (Brodal, 2010a).
The Cerebellum
The cerebellum (back of the brain), also known as ‘the little brain’, is located underneath the occipital lobe. It is the second-largest part of the brain and contains over half the brain’s neurons (Carey, 2018). The cerebellum is highly folded, divided into two hemispheres, and necessary for carrying out various functions. It belongs to the motor system and involves functions such as the coordination and execution of voluntary movements, posture and balance (Brodal, 2010a).
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1 2
3 5 4
6
8
presynaptic postsynaptic
1: Axon 2: Axon terminal 3: Dendrite 4: Synaptic terminals 5: Cell body 5: Synaptic vesicles 6: Cleft
7: Receptor
7
Figure 3 - The anatomy of a neuron.
Adapted from Jansen and Glover, 2020
The nervous system is made up of two types of cells, called neurons and glia. The neurons sense and respond to internal changes in the body and external changes in the environment. (Crossman, Neary and Crossman, 2019). The cells encode and conduct information, sometimes over substantial distances and transmit signals to other neurons or non-neutral tissues such as muscles or glandular cells. The neuron has electrical properties and is the functional capabilities of the nervous system (Mancall, Brock and Gray, 2011).
Neurons are some of the longest-lived cells in the body. In a recent study, neurons continued to live past their life expectancy after being transplanted from a donor mouse to a longer-living rat. This research suggests that the organism’s life length determines the neurons life.
(Magrassi, Leto and Rossi, 2013)
Most neurons consist of a central mass of cytoplasm within a limiting cell membrane, termed the soma, or cell body which is the cells life support. Numerous branched processes known as neurites extend out from the soma. The dendrites pick up messages from other cells and send information towards the soma. The axon, usually much longer than other processes, transmits electrical impulses away from the cell body to other cells (Mancall, Brock and Gray, 2011).
Different types of neurons are classified by their number of dendrites and axons extending out from the cell body. The vast majority of neurons are multipolar neurons, with three or more processes. The multipolar neurons characteristically have one axon and several dendrites that extend from the soma. Most motor neurons or efferent neurons are multipolar. They transmit impulses from the central nervous system and out to the body’s muscles and glands. Interneuron neurons (association neurons) are commonly multipolar neurons located in the central nervous system. They transmit impulses between sensory and motor neurons.
Bipolar neurons have a centrally placed cell body with two processes, an axon and a single dendrite, extending from opposite sides. Bipolar neurons are located in sensory places like the afferent pathways of the visual, auditory, and vestibular systems. Unipolar neurons have one single process emerging from the soma, which divides into dendritic and axonal branches. Sensory neurons or afferent neurons are unipolar. Neurons of this type receive messages transmit impulses from sensory receptors, and send them towards the nervous system. (Watson, Kirkcaldie and Paxinos, 2010).
5.1 Neurons
Sofie Gustafsson 38 of 127 Master Thesis 2021 Synapses
The synapse or the ‘gap’ is the communication links between cells.
A nerve cell is separated, and the cell body has an electrochemical messaging system where neurons communicate by receiving and sending information across the nervous system. The transmission of information happens when signal molecules (neurotransmitters) are released and passes signals to other cells.
First, an action potential sends an electrical message to the synapse and then the signal is translated and sends it to another neuron. The process in which synaptic inputs are identified and nerve impulses are generated is called synaptic integration. The human brain has 100 million neurons, and each of these has 1000 to 10,000 synapses. Each of the hundreds of trillions of synapses can change and adapt its strength based on experience. This process gives the human brain the ability to learn and remember.
Nerves that send out signals are called presynaptic neurons, and the neuron that receives signals are called the postsynaptic neuron. Most neurons are, however, both presynaptic and postsynaptic. Two main types of synapses are called electrical- and chemical synapses. Electric coupling (gap junctions) are, however, most common in the glia. An electrical synapse sends an ion directly from the cytoplasm of one nerve cell to another over a gap junction to transmit neurological signals.
Chemical synapses turn electrical signals into chemical signals using neurotransmitters and then converts them back to electrical signals. This process gives the synapse the ability to modify, amplify, inhabit or split signals. Neurotransmitters help the brain to regulate necessary functions in the body by targeting specific cells (Crossman and Neary, 2014).
Glia cells
Up until recently, scientists believed that the brain contains a higher number of glial cells than neurons. Recent findings, however, show that there is roughly a 1:1 ratio between neurons and glial cells (von Bartheld, Bahney and Herculano-Houzel, 2016). Glia has also proven to be far more important than previously expected. (Watson, Kirkcaldie and Paxinos, 2010) New research about the glia is rapidly emerging, but the complete understanding of glial cells functions is still unclear (Eroglu and Barres, 2010). A recent study concluded that glial cells are vital to all functions of the CNS and PNS. The cells play an essential part in developing the nervous system, the survival and metabolic support of neurons, and the interaction between cells that regulate signal transmission and plasticity.
(Zuchero and Barres, 2015).
Sensory-motor integration
The nervous system has three principal and overlapping functions:
sensory (afferent) input, integration and motor (efferent) output.
Sense organs or receptors reactions are based on sensory information or stimuli from both the general and special senses. The energy of the stimulus is translated and becomes nerve impulses. (Per Brodal, 2010) For example, if someone taps your shoulder, the sensory receptors on the skin detects the touch of a hand; that information is called sensory input.
Interneurons processes that input and decides the response in a process called integration. The motor output activates the body by sending directions from the nervous system to effector organs such as muscles and glands (Mancall, Brock and Gray, 2011). The motor division includes the voluntary (somatic) nervous system that rules the skeletal muscle movement and the involuntary (autonomic) nervous system (Crossman, Neary and Crossman, 2019) .
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Figures
Figure 1 - An overview of the CNS and the PNS.
Adapted from Djebbara, 2020
Figure 2 - The brains anatomy.
Adapted from iMotions, 2019 Figure 3 - The anatomy of a neuron.
Adapted from Jansen and Glover, 2020 32
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BJERKNES, T. L. & MOSER, M. 2019. A sense of place. Biologist, 66, p. 10-13.
BRODAL, P. 2010a. 6. Parts of the Nervous System. The Central Nervous System: Structure and Function. New York: Oxford University Press.
BRODAL, P. 2010b. Introduction. The Central Nervous System: Structure and Function. New York: Oxford University Press.
CAREY, J. 2018. Brain facts. A primer on the brain and nervous system. 2018 ed.
CROSSMAN, A. R. & NEARY, D. 2014. Neuroanatomy E-book: an illustrated colour text, Elsevier Health Sciences.
DJEBBARA, Z. 2020. Expecting space: an enactive and active inference approach to transitions.
MANCALL, E. L., BROCK, D. G., 2011. Gray’s clinical neuroanatomy: the anatomic basis for clinical neuroscience, ELSEVIER INDIA.
HYDER, F., ROTHMAN, D. L. & BENNETT, M. R. 2013. Cortical energy demands of signaling and nonsignaling components in brain are conserved across mammalian species and activity levels. Proceedings of the National Academy of Sciences, 110, 3549-3554.
IMOTIONS 2019. Electroencephalography - The Complete Pocket Guide. iMotions.
JANSEN, J. & GLOVER, J. 2020. Synapse [Online]. Store medisinske leksikon. Available: https://sml.snl.no/synapse [Accessed April 3rd 2021].
KAPALKA, G. M. 2010. Chapter 3 - Pharmacodynamics. In: KAPALKA, G. M. Nutritional and Herbal Therapies for Children and Adolescents. San Diego: Academic Press.
LA ROSA, C., PAROLISI, R. & BONFANTI, L. 2020. Brain structural plasticity: from adult neurogenesis to immature neurons.
Frontiers in neuroscience, 14, 75.
MAGRASSI, L., LETO, K. & ROSSI, F. 2013. Lifespan of neurons is uncoupled from organismal lifespan. Proceedings of the National Academy of Sciences, 110, 4374-4379.
MANCALL, E. L. & BROCK, D. G. 2011. Overview of the Organization of the Nervous System. Gray’s Clinical Neuroanatomy:
The anatomic basis for clinical neuroscience Elsevier Health Sciences.
REA, P. 2015. Chapter 1 - Introduction to the Nervous System. In: REA, P. Essential Clinical Anatomy of the Nervous System.
San Diego: Academic Press.
VON BARTHELD, C. S., BAHNEY, J. & HERCULANO‐HOUZEL, S. 2016. The search for true numbers of neurons and glial cells in the human brain: a review of 150 years of cell counting. Journal of Comparative Neurology, 524, 3865-3895.
References
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6. Assessing the Quality of Research
Recently there has been raised concerns across several fields of science regarding the accuracy of research findings, and some suggest that ongoing reproducibility crisis. A survey conducted by Nature in 2016 involved 1,576 researchers who participated in an online questionnaire about reproducibility in research (Baker, 2016). The results concluded that more than 70% of researchers had unsuccessfully tried to reproduce another investigator experiment. 90 % of the participants thought there was a slight or significant reproducibility crisis, and only 3 % believed there was no crisis.
There is, however, an ongoing disagreement between researchers about the severity of this ‘crises’. Some claim that most research papers present false results (Ioannidis, 2005, Smaldino and McElreath, 2016),, whiles others argue that this statement is either untrue or yet to be proven (Goodman and Greenland, 2007). Fanelli, on the other hand, argues that
“’he new ‘science is in crisis’ narrative is not only empirically unsupported but also quite obviously counterproductive’ (2018). The author refers to similar beliefs that have recurred throughout history and continue by claiming that such statements spread discouragement among the next generations of researchers, who should instead be motivated to produce higher quality research.
Transparency and reproducibility
Transparency and reproducibility are essential in current and future science research (Begley and Ioannidis, 2015). Selective and inadequate reporting as well as selective analysis of conditions limits transparency in research.
The ability to replicate findings ensures transparency and provides an understanding of how the original study has been conducted. A study in the field of psychology examined the replications of 100 experimental and correlational studies to determine to what extent reproducibility defines current research. The investigators argues that there is a need for high- powered replications of prominent effects and the research concluded that “a large portion of replications produced weaker evidence for the original findings despite using materials provided by the original authors, review in advance for methodological fidelity, and high statistical power to detect the original effect sizes” (Collaboration, 2015).
Sample Size
An adequate sample size is crucial to the avoidance of research errors.
Sample size calculations are performed to ensure that research projects are sufficiently powered and decrease the likelihood of type II errors (false negatives). Systematic reviews from different disciplines do, however, reveal that underpowered studies continue to be published. A systematic
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x variable y
y x
x
Negative Positive
-1.0 0.0 1.0
Strength of the relationship
Direction of the relationship
y variable
Figure 1 - Correlation coefficients.
The authors argue that there are several reasons why researchers choose small sample sizes. Conducting comprehensive studies requires generous amounts of resources, time, which can cause researchers to select smaller sample sizes. Investigators might also be motivated by personal gain and recognition to speed up the research process, as published studies can lead to new career opportunities.
Bigger is, however, not always better. Too large sample sizes can also cause problems resulting in sampling errors and inaccurate and lacking information. In some cases, big data can even enlarge the bias.
Representativeness is generally more important than big data and large sample sizes. A group of participant that does not represent the population can cause misleading results (Kaplan et al., 2014).
Probability and Effect Size
Conducting comprehensive studies can be both time-consuming, costly and requires a lot of hard work. Generous amounts of recourses are invested into research projects, and, understandably, investigators hope for significant findings (Larson and Carbine, 2017). Data can, however, be manipulated; “if you torture your data long enough, they will tell you whatever you want to hear” (Mills, 1993, p. 1196). Honest exploratory studies should document the number of comparisons, as multiple comparisons can result in false statistically significant findings. In all statistical tests, there is a chance of a false positive (type I error) result (Mills, 1993). The statistically significant threshold usually is 0.05, but when running multiple tests, the I error increases (Sainani, 2009).
P-values illustrates how likely a finding occurs due to chance (Mills, 1993). Eva Skovlund, professor of medical statistics, argues that a p-value cannot be calculated without a specified question. She continues by suggesting an implementation process; 1) ask a question, 2) determine the significance level, 3) formulate the null hypothesis and an alternative hypothesis, 4) perform the experiment, 6) compare the p-value and the significance level, discard null hypothesis if p < 0.05. Post hoc data analysis and significance tests pursued due to unexpected observations should be clearly stated in the study, as the p-value is less reliable (Skovlund, 2013).
